Foodomics advanced mass spectrometry in modern food science and nutrition edited by alejandro cifuentes

Library of Congress Cataloging-in-Publication Data Foodomics : advanced mass spectrometry in modern food science and nutrition / edited by... The interest of the scientific community in m

FOODOMICS

Series Editors

Dominic M Desiderio

Departments of Neurology and Biochemistry

University of Tennessee Health Science Center

Nico M M Nibbering

Vrije Universiteit Amsterdam, The Netherlands

A complete list of the titles in this series appears at the end of this volume

Laboratory of Foodomics (CIAL)

National Research Council (CSIC)

Madrid, Spain

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Library of Congress Cataloging-in-Publication Data

Foodomics : advanced mass spectrometry in modern food science and nutrition / edited by

To the three women in my life, Susana, Claudia and Fernanda, every day they

make of this world a better place to be.

A las tres mujeres de mi vida, Susana, Claudia y Fernanda, porque cada d´ıa

ellas hacen de este mundo un lugar mejor donde vivir.

Mar´ıa del Carmen Mena and Juan Pablo Albar

2.3 The Move from Shotgun to Targeted Proteomics Approaches 342.4 New Instrumental Methods for Proteomics 40

vii

viii CONTENTS

Gianluca Picariello, Gianfranco Mamone, Francesco Addeo, Chiara Nitride,

and Pasquale Ferranti

3.1 Introduction: What is Food Allergy? 693.2 Food Allergy: Features and Boundaries of the Disease 703.3 Immunopathology of Food Allergy and Role of Proteomics 713.4 Identification of Food Allergy Epitopes 733.5 Expression Proteomics and Functional Proteomics in

3.6 Identification of Allergens in Transformed Products 85

Ashraf G Madian, Elsa M Janle, and Fred E Regnier

4.2 Methods for Studying the Efficacy of Antioxidants 1024.3 Strategies Used for Proteomic Analysis of Carbonylated Proteins

4.5 Quantification of Carbonylation Sites 1114.6 Biomedical Consequence of Protein Oxidation and the Impact

4.7 Redox Proteomics and Testing the Efficacy of Antioxidants 113

Jos´e M Gallardo, M´onica Carrera, and Ignacio Ortea

5.3 Species Identification and Geographic Origin 1325.4 Detection and Identification of Spoilage and Pathogenic

6 Proteomics in Nutritional Systems Biology: Defining Health 167

Martin Kussmann and Laurent Fay

6.2 From Food Proteins to Nutriproteomics 1716.3 Nutritional Peptide and Protein Bioactives 1726.4 Nutritional Peptide and Protein Biomarkers 1746.5 Ecosystem-Level Understanding of Nutritional Host Health 178

Wendy R Russell and Sylvia H Duncan

Clara Ib´a˜nez and Carolina Sim´o

9.3 Metabolomics in Nutrition-Related Studies 2539.4 Diet/Nutrition and Disease: Metabolomics Applications 2599.5 Other Applications in Nutritional Metabolomics 261

x CONTENTS

Max Scherer, Alastair Ross, Sofia Moco, Sebastiano Collino, Franc¸ois-Pierre

Martin, Jean-Philippe Godin, Peter Kastenmayer, and Serge Rezzi

Anna Arola-Arnal, Josep M del Bas, Antoni Caimari, Anna Crescenti,

Francesc Puiggr`os, Manuel Su´arez, and Llu´ıs Arola

Isabel Bondia-Pons and Tuulia Hy¨otyl¨ainen

12.1 Definition and Analytical Challenges in Lipidomics 35112.2 Lipidomics in Nutrition and Health Research 360

Susan J Duthie

13.3 Measuring Folates in Human Biomonitoring 38513.4 Folate and Colon Cancer: Establishing Mechanisms of Genomic

Instability Using a Combined Proteomic and Functional Approach 38713.5 Folate Deficiency and Abnormal DNA Methylation: A Common

Mechanism Linking Cancer and Atherosclerosis 394

14 Metabolomics Markers in Acute and Endurance/Resistance

Sonia Medina, D´ebora Villa˜no, Jos´e Ignacio Gil, Cristina Garc´ıa-Viguera,

Federico Ferreres, and Angel Gil-Izquierdo

14.2 Metabolomics Consequences of Physical Activity: Metabolites

and Physiological Pathways Affected 40714.3 Metabolomics and Physical Activity: Effect of the Diet 41014.4 Concluding Remarks and Future Perspectives 411

D´ebora Villa˜no, Sonia Medina, Jos´e Ignacio Gil, Cristina Garc´ıa-Viguera,

Federico Ferreres, Francisco A Tom´as-Barber´an, and Angel Gil-Izquierdo

15.2 Use of Metabolomics in Nutritional Trials 41615.3 Statistic Tools in Nutritional Metabolomics 42115.4 Metabolomics from Clinical Trials after Intake of

Marcela A Erazo, Antonia Garc´ıa, Francisco J Rup´erez, and Coral Barbas

Jose A Mendiola, Mar´ıa Castro-Puyana, Miguel Herrero, and Elena Ib´a˜nez

18.1 Basic Concepts of Foodomics (and How to Make it Greener) 47118.2 Basic Concepts of Green Chemistry 47218.3 Green Processes to Produce Functional Food Ingredients 47618.4 Development of Green Analytical Processes for Foodomics 48218.5 Comparative LCA Study of Green Analytical Techniques:

Thomas Skov and Søren B Engelsen

The impressive analytical developments achieved at the end of the twentieth tury have made possible the sequencing of nearly the whole human genome at the

cen-beginning of the twenty-first century, opening the so-called postgenomic era These

advances have made feasible analytical instruments and methodological ments that were unthinkable a few decades ago These impressive developments havetraditionally found their first application in the biotechnological or biochemical fieldmany times linked to pharmaceutical, medical, or clinical needs The huge amount

develop-of money allocated to these fields develop-of research is logically an additional push to beconsidered when selecting the area in which a new analytical method can be probed,

a good way to compensate the efforts behind any innovative analytical development

As a result, biotech, pharmaceutical, and clinical related industries have usually beenthe first targets for analytical chemists and instrumentation companies This has leftfood analysis overshadowed and connected to the use of more traditional analyticalapproaches Nowadays, boundaries among the different research fields are becom-ing more and more diffuse giving rise to impressive possibilities in the emerginginterdisciplinary areas, for example, health and food As a result, researchers in foodscience and nutrition are being pushed to move from classical methodologies to moreadvanced strategies usually borrowing methods well established in medical, pharma-cological, and/or biotechnology research This trend has generated the emergence ofnew areas of research for which a new terminology is required In this context, our

group defined a few years ago Foodomics, as a discipline that studies the food and

nutrition domains through the application of advanced omics technologies to improve consumer’s well-being, health, and confidence The main idea behind the use of this

new term has been not only to use it as a flag of the new times for food analysis but also

to highlight that the investigation into traditional and new problems in food analysis

xiii

xiv PREFACE

in the postgenomic era can find exciting opportunities and new answers through theuse of genomics, transcriptomics, epigenetics, proteomics, and metabolomics tools

Indeed, Foodomics is opening a new and unexpected land still wild, still unexplored,

to a new generation of researchers who, using the everyday more powerful omicstechnologies, can find original search possibilities and innovative answers to crucialquestions not only related to food science but also related to its complex links withour health

The interest of the scientific community in modern food analysis and Foodomics,

and the different trends in this hot area of research are well documented in the 20

chapters that compose this volume on “Foodomics: Advanced Mass Spectrometry in

Modern Food Science and Nutrition”, the first book devoted to this new discipline in

which the authors present their advanced perspective of the topic Namely, in the firstchapter the principles of Foodomics are presented, the next five chapters (chapter 2

to 6) are devoted to proteomics applications in Foodomics, including a description

of modern instruments and methods for proteomics, proteomic-based techniques forfood science and food allergens characterization, examination of antioxidant foodsupplements using advanced proteomics methods and proteomics in nutritional sys-tems biology The next two chapters (chapters 7 and 8) are devoted to the description

of advanced MS-based methodologies to study transgenic foods development andcharacterization and the microbial metabolome The following nine chapters (chap-ters 9 to 17) are devoted to metabolomics developments in Foodomics with specialemphasis on the possibilities of MS-based metabolomics in nutrition and healthresearch, for food safety, quality, and traceability, the investigations on future person-alized nutrition, the study of the effect of the diet on acute and endurance exercise,the investigation on diet-related diseases, and the study on how Foodomics impactoptimal nutrition or can provide crucial information on micronutrients (the case offolates), phenolic compounds as functional ingredients, and lipids (lipidomics) Thefollowing two chapters (chapters 18 and 19) present the main principles of GreenFoodomics and the use of chemometrics in mass spectrometry and Foodomics Thelast chapter of the book is devoted to the description of the possibilities of systemsbiology in food and nutrition research

As editor of this book devoted to “Foodomics: Advanced Mass Spectrometry in

Modern Food Science and Nutrition”, I would like to thank all the authors for their

suitable contributions, Dom Desiderio for inviting me to prepare this piece of work,Michael Leventhal for his help and support, and to those in the John Wiley & Sonsteam who contributed their effort to the preparation of this volume

Alejandro Cifuentes

Francesco Addeo, Dipartimento di Scienza degli Alimenti, University of Naples

Federico II, Naples, Italy

Juan Pablo Albar, Functional Proteomics Group, Centro Nacional de

Biotec-nolog´ıa–CSIC, Madrid, Spain

Llu´ıs Arola, Centre Tecnol`ogic de Nutrici´o i Salut (CTNS), TECNIO, Reus, Spain;

Departament de Bioqu´ımica i Biotecnologia, Nutrigenomics Research Group, versitat Rovira i Virgili, Tarragona, Spain

Uni-Anna Arola-Arnal, Departament de Bioqu´ımica i Biotecnologia, Nutrigenomics

Research Group, Universitat Rovira i Virgili, Tarragona, Spain

Coral Barbas, Center for Metabolomics and Bioanalysis (CEMBIO), Facultad de

Farmacia, Universidad CEU San Pablo, Boadilla del Monte, Madrid, Spain

Isabel Bondia-Pons, Quantitative Biology and Bioinformatics, VTT Technical

Research Centre of Finland, Espoo, Finland

Antoni Caimari, Centre Tecnol`ogic de Nutrici´o i Salut (CTNS), TECNIO, Reus,

Spain

M´onica Carrera, Institute of Molecular Systems Biology, ETH Z¨urich, Z¨urich,

Switzerland

Mar´ıa Castro-Puyana, Laboratory of Foodomics, Institute of Food Science

Research (CIAL), National Research Council (CSIC), Madrid, Spain

xv

xvi CONTRIBUTORS

Alejandro Cifuentes, Laboratory of Foodomics, Institute of Food Science Research

(CIAL), National Research Council (CSIC), Madrid, Spain

Sebastiano Collino, BioAnalytical Science, Nestle Research Center, Lausanne,

Susan J Duthie, Natural Products Group, Division of Lifelong Health, Rowett

Institute of Nutrition and Health, University of Aberdeen, Aberdeen, UK

Søren B Engelsen, Faculty of Science, University of Copenhagen, Copenhagen,

Denmark

Marcela A Erazo, Center for Metabolomics and Bioanalysis (CEMBIO), Facultad

de Farmacia, Universidad CEU San Pablo, Boadilla del Monte, Madrid, Spain

Laurent Fay, R&D Infant Formulae, Nestl´e Nutrition, Vevey, Switzerland

Pasquale Ferranti, Istituto di Scienze dell’Alimentazione, CNR, Avellino, Italy;

Dipartimento di Scienza degli Alimenti, University of Naples Federico II, Naples,Italy

Federico Ferreres, Department of Food Science and Technology, CEBAS-CSIC,

Murcia, Spain

Jose M Gallardo, Marine Research Institute, CSIC, Vigo, Pontevedra, Spain Antonia Garc´ıa, Center for Metabolomics and Bioanalysis (CEMBIO), Facultad de

Farmacia, Universidad CEU San Pablo, Boadilla del Monte, Madrid, Spain

Virginia Garc´ıa-Ca ˜nas, Laboratory of Foodomics, Institute of Food Science

Research (CIAL), National Research Council (CSIC), Madrid, Spain

Cristina Garc´ıa-Viguera, Department of Food Science and Technology,

CEBAS-CSIC, Murcia, Spain

Jos´e Ignacio Gil, Service of Radiodiagnostic, Mammary Pathology Department,

Hospital Jos´e Mar´ıa Morales Meseguer, Murcia, Spain

Angel Gil-Izquierdo, Department of Food Science and Technology, CEBAS-CSIC,

Murcia, Spain

Lausanne, Switzerland

Miguel Herrero, Laboratory of Foodomics, Institute of Food Science Research

(CIAL), National Research Council (CSIC), Madrid, Spain

Tuulia Hy¨otyl¨ainen, Quantitative Biology and Bioinformatics, VTT Technical

Research Centre of Finland, Espoo, Finland

Clara Ib´a ˜nez, Laboratory of Foodomics, Institute of Food Science Research (CIAL),

National Research Council (CSIC), Madrid, Spain

Elena Ib´a ˜nez, Laboratory of Foodomics, Institute of Food Science Research (CIAL),

National Research Council (CSIC), Madrid, Spain

Elsa M Janle, Department of Foods and Nutrition, Purdue University, West

Lafayette, Indiana, USA

Peter Kastenmayer, BioAnalytical Science, Nestle Research Center, Lausanne,

Switzerland

Martin Kussmann, Proteomics/Metabonomics Core, Nestl´e Institute of Health

Sciences, Lausanne, Switzerland; Faculty of Science, Aarhus University, Aarhus,Denmark

Ashraf G Madian, Department of Chemistry, Purdue University, West Lafayette,

Indiana, USA

Gianfranco Mamone, Istituto di Scienze dell’Alimentazione, CNR, Avellino, Italy

Lausanne, Switzerland

Sonia Medina, Department of Food Science and Technology, CEBAS-CSIC,

Murcia, Spain

Mar´ıa del Carmen Mena, Functional Proteomics Group, Centro Nacional de

Biotecnolog´ıa–CSIC, Madrid, Spain

Jos´e A Mendiola, Laboratory of Foodomics, Institute of Food Science Research

(CIAL), National Research Council (CSIC), Madrid, Spain

Switzerland

Chiara Nitride, Dipartimento di Scienza degli Alimenti, University of Naples

Fed-erico II, Naples, Italy

Matej Oreˇsiˇc, Systems Biology and Bioinformatics, VTT Technical Research

Cen-tre of Finland, Espoo, Finland

Ignacio Ortea, Health Research Institute of Santiago de Compostela, A Coru˜na,

Spain

Francisco J Rup´erez, Center for Metabolomics and Bioanalysis (CEMBIO),

Fac-ultad de Farmacia, Universidad CEU San Pablo, Boadilla del Monte, Madrid, Spain

Wendy R Russell, Rowett Institute of Nutrition and Health, University of Aberdeen,

Carolina Sim´o, Laboratory of Foodomics, Institute of Food Science Research

(CIAL), National Research Council (CSIC), Madrid, Spain

Manuel Su´arez, Departament de Bioqu´ımica i Biotecnologia, Nutrigenomics

Research Group, Universitat Rovira i Virgili, Tarragona, Spain

Francisco A Tom´as-Barber´an, Department of Food Science and Technology,

CEBAS-CSIC, Murcia, Spain

Alberto Vald´es, Laboratory of Foodomics, Institute of Food Science Research

(CIAL), National Research Council (CSIC), Madrid, Spain

D´ebora Villa ˜no, Department of Food Science and Technology, CEBAS-CSIC,

Murcia, Spain

called Globalization and the movement of food and related raw materials worldwide,

which are generating contamination episodes that are also becoming global Anadditional difficulty is that many products contain multiple and processed ingredients,which are often shipped from different parts of the world, and share common storagespaces and production lines As a result, ensuring the safety, quality, and traceability

of food has never been more complicated and necessary than today

The first goal of food science has traditionally been, and still is, to ensure foodsafety To meet this goal, food laboratories are being pushed to exchange their classicalprocedures for modern analytical techniques that allow them to give an adequateanswer to this global demand Besides, the new European regulations in the EuropeanUnion countries (e.g., Regulation EC 258/97 or EN 29000 and subsequent issues),the Nutrition Labeling and Education Act in the USA, and the Montreal Protocolhave had a major impact on food laboratories Consequently, more powerful, cleaner,and cheaper analytical procedures are now required by food chemists, regulatoryagencies, and quality control laboratories These demands have increased the need

Foodomics: Advanced Mass Spectrometry in Modern Food Science and Nutrition, First Edition.

Edited by Alejandro Cifuentes.

© 2013 John Wiley & Sons, Inc Published 2013 by John Wiley & Sons, Inc.

1

2 FOODOMICS: PRINCIPLES AND APPLICATIONS

for more sophisticated instrumentation and more appropriate methods able to offerbetter qualitative and quantitative results while increasing the sensitivity, precision,specificity, and/or speed of analysis

Currently, there is also a general trend in food science toward the connectionbetween food and health Thus, food is considered today not only a source of energybut also an affordable way to prevent future diseases The number of opportunities(e.g., new methodologies, new generated knowledge, new products) derived from thistrend is impressive and it includes, for example, the possibility to account for foodproducts tailored to promote the health and well-being of groups of population identi-fied on the basis of their individual genomes Interaction of modern food science andnutrition with disciplines such as pharmacology, medicine, or biotechnology providesimpressive new challenges and opportunities As a result, researchers in food scienceand nutrition are moving from classical methodologies to more advanced strategies,and usually borrow methods well established in medical, pharmacological, and/orbiotechnology research As a result, advanced analytical methodologies, “omics”

approaches, and bioinformatics—frequently together with in vitro, in vivo, and/or

clinical assays—are applied to investigate topics in food science and nutrition thatwere considered unapproachable few years ago

In modern food science and nutrition, terms such as nutrigenomics, ics, nutritional genomics, transgenics, functional foods, nutraceuticals, geneticallymodified (GM) foods, microbiomics, toxicogenomics, nutritranscriptomics, nutripro-teomics, nutrimetabolomics, and systems biology are expanding This novelty hasalso brought about some problems related to the poor definition of part of this termi-nology or their low acceptance, probably due to the difficulty to work in a developingfield in which several emerging strategies are frequently put together

Although the term Foodomics is being used in different web pages and scientific

meet-ings since 2007 (see e.g., Slater and Wilson, 2007 or Capozzi and Placucci, 2009),

Foodomics was for the first time defined in an SCI journal in 2009 as a new discipline that studies the food and nutrition domains through the application of advanced omics technologies to improve consumer’s well-being, health, and confidence (Cifuentes,

2009; Herrero et al., 2010, 2012) Thus, Foodomics is not only an useful concept thatcomprises in a simple and straightforward way all of the emerging terms aforemen-tioned (e.g., nutrigenomics, nutrigenetics, microbiomics, toxicogenomics, nutritran-

scriptomics, nutriproteomics, nutrimetabolomics), but more importantly, Foodomics

is a global discipline that includes all the working areas in which food (including nutrition) and advanced omics tools are put together.

A representation of the areas covered by Foodomics and the tools employed can

be seen in Figure 1.1 Just to name a few topics that could be addressed by thisnew discipline, Foodomics would help: (a) to understand the gene-based differencesamong individuals in response to a specific dietary pattern following nutrigeneticapproaches; (b) to understand the biochemical, molecular, and cellular mechanismsthat underlie the beneficial or adverse effects of certain bioactive food components

FIGURE 1.1 Foodomics: covered areas and tools.

following nutrigenomic approaches; (c) to determine the effect of bioactive foodconstituents on crucial molecular pathways; (d) to know the identity of genes thatare involved in the previous stage to the onset of the disease, and, therefore, possiblemolecular biomarkers; (e) to establish the global role and functions of gut micro-biome, a topic that is expected to open an impressive field of research in the nearfuture; (f) to carry out the investigation on unintended effects in GM crops; (g) tounderstand the stress adaptation responses of food-borne pathogens to ensure foodhygiene, processing, and preservation; (h) to investigate the use of food microor-ganisms as delivery systems including the impact of gene inactivation and deletionsystems; (i) in the comprehensive assessment of food safety, quality, and traceabil-ity ideally as a whole; (j) to understand the molecular basis of biological processeswith agronomic interest and economic relevance, such as the interaction betweencrops and its pathogens, as well as physicochemical changes that take place dur-ing fruit ripening; and (k) to fully understand postharvest phenomena through aglobal approach that links genetic and environmental responses and identifies theunderlying biological networks In this regard, it is expected that the new omicstechnologies combined with systems biology, as proposed by Foodomics, can leadpostharvest research into a new era The interest in Foodomics also coincides with aclear shift in medicine and biosciences toward prevention of future diseases throughadequate food intakes, and the development of the so-called functional foods that arediscussed below

4 FOODOMICS: PRINCIPLES AND APPLICATIONS

As can be seen in Figure 1.1, Foodomics involves the use of multiple tools to dealwith its different subdisciplines and applications Thus, the use of omics tools such

as genomics, epigenomics, transcriptomics, proteomics, and metabolomics is a must

in this new discipline Although a detailed description on these tools is out of thescope of this chapter, some fundamentals about these techniques are provided below.Epigenomics studies the mechanisms of gene expression that can be maintainedacross cell divisions, and thus the life of the organism, without changing the DNAsequence The epigenetic mechanisms are related to the changes induced (e.g., bytoxins or bioactive food ingredients) in gene expression via altered DNA methylationpatterns, altered histone modifications, or noncoding RNAs, including small RNAs

In mammals, many dietary components, including folate, vitamin B6, vitamin B12,betaine, methionine, and choline, have been linked to changes in DNA methylation.These nutrients can all affect the pathways of one-carbon metabolism that determinethe amount of available S-adenosylmethionine, which is the methyl donor for DNAmethylation and histone methylation Although it is too early to apply epigeneticalterations that are induced by dietary ingredients as biomarkers in public healthand medicine, research in this area is expected to be boosted by the expanding use

of next-generation DNA sequencing technologies Applications include chromatinimmunoprecipitation followed by DNA sequencing (ChIP–seq) to assess the genomicdistribution of histone modifications, histone variants and nuclear proteins, and globalDNA methylation analysis through the sequencing of bisulphite-converted genomicDNA Combined with appropriate statistical and bioinformatic tools, these methodswill permit the identification of all the loci that are epigenetically altered

Regarding transcriptomics, the global analysis of gene expression offers sive opportunities in Foodomics (e.g., for the identification of the effect of bioactivefood constituents on homeostatic regulation and how this regulation is potentiallyaltered in the development of certain chronic diseases) Two conceptually differentanalytical approaches have emerged to allow quantitative and comprehensive analy-sis of changes in mRNA expression levels of hundreds or thousands of genes Oneapproach is based on microarray technology, and the other group of techniques isbased on DNA sequencing Next, typically real-time PCR is applied to confirm theup- or down-regulation of a selected number of genes

impres-In proteomics, the huge dynamic concentration range of proteins in biologicalsamples causes many detection difficulties because many proteins are below thesensitivity threshold of the most advanced instruments For this reason, fractionationand subsequent concentration of the proteome is often needed Besides, the use anddevelopment of high-resolving separation techniques as well as highly accurate massspectrometers is nowadays essential to solve the proteome complexity Currently,more than a single electrophoretic or chromatographic step is used to separate thethousands of proteins found in a biological sample This separation step is followed

by analysis of the isolated proteins (or peptides) by mass spectrometry (MS) viathe so-called “soft ionization” techniques, such as electrospray ionization (ESI) andmatrix-assisted laser desorption/ionization (MALDI), combined with the everyday

more powerful mass spectrometers Two fundamental analytical strategies can be

employed: the bottom-up and the top-down approach Both methodologies differ on

the separation requirements and the type of MS instrumentation New proteomicapproaches based on array technology are also being employed Protein microarrayscan be composed by recombinant protein molecules or antibodies immobilized in ahigh-density format on the surface of a substrate material There are two major classes

of protein micro- (nano-) arrays: analytical and functional protein microarrays, beingthe antibody-based microarray the most common platform in proteomic studies.Metabolome can be defined as the full set of endogenous or exogenous lowmolecular weight metabolic entities of approximately<1000 Da (metabolites), and

the small pathway motifs that are present in a biological system (cell, tissue, organ,organism, or species) Unlike nucleic acid or protein-based omics techniques, whichintend to determine a single chemical class of compounds, metabolomics has to dealwith very different compounds of very diverse chemical and physical properties.Moreover, the relative concentration of metabolites in the biological fluids can varyfrom millimolar (or higher) to picomolar level, making it easy to exceed the linearrange of the analytical techniques employed Metabolites are, in general, the finaldownstream products of the genome, and reflect most closely the operation of thebiological system, its phenotype The analysis of metabolic patterns and the changes

in the metabolism in the nutrition field can be, therefore, very interesting to locate;for example, variations in different metabolic pathways due to the consumption ofdifferent compounds in the diet One of the main challenges in metabolomics is toface the complexity of any metabolome, usually composed by a huge number ofcompounds of very diverse chemical and physical properties (sugars, amines, aminoacids, organic acids, steroids, etc.) Sample preparation is especially important inmetabolomics, because the procedure used for metabolite extraction has to be robustand highly reproducible Sample preparation will depend on the sample type andthe targeted metabolites of interest (fingerprinting or profiling approach) Moreover,

no single analytical methodology or platform is applicable to detect, quantify, andidentify all metabolites in a certain sample Two analytical platforms are currentlyused for metabolomic analyses: MS- and NMR-based systems These techniques,either stand-alone or combined with separation techniques (typically, LC-NMR, GC-

MS, LC-MS, and CE-MS) can produce complementary analytical information toattain more extensive metabolome coverage There are three basic approaches thatcan be used in metabolomics: target analysis, metabolic profiling, and metabolic fin-gerprinting Target analysis aims the quantitative measurement of selected analytes,such as specific biomarkers or reaction products Metabolic profiling is a nontargetedstrategy that focuses on the study of a group of related metabolites or a specificmetabolic pathway It is one of the basic approaches to phenotyping, because thestudy of metabolic profiles of a cell gives a more accurate description of a pheno-type Meanwhile, metabolic fingerprinting does not aim to identify all metabolites,but to compare the patterns of metabolites that change in response to the cellularenvironment

Due to the huge amount of data usually obtained from omics studies, it has beennecessary to develop strategies to convert the complex raw data obtained into useful

6 FOODOMICS: PRINCIPLES AND APPLICATIONS

information Thus, bioinformatics has also become a crucial tool in Foodomics Overthe last years, the use of biological knowledge accumulated in public databases bymeans of bioinformatics allows to systematically analyze large data lists in an attempt

to assemble a summary of the most significant biological aspects Also, statisticaltools are usually applied for exploratory data analysis to determine correlations amongsamples (which can be caused by either a biological difference or a methodologicalbias), for discriminating the complete data list and reducing it with the most relevantones for biomarkers discovery, etc

AND DRAWBACKS

Although there is still a large number of gaps to be filled in our current knowledge

on food science and nutrition, the great analytical potential of Foodomics can help

resolve many issues and questions related to food safety, traceability, quality, newfoods, transgenic foods, functional foods, nutraceuticals, etc

Foodomics can help solve some of the new challenges that modern food safety,quality, and traceability have to face These challenges encompass the multiple anal-yses of contaminants and allergens; the establishment of more powerful analyticalmethodologies to guarantee food origin, traceability, and quality; the discovery ofbiomarkers to detect unsafe products; the capability to detect food safety problemsbefore they grow and affect more consumers; etc

Although this book includes a chapter devoted to transgenic foods, a brief outline

on this topic is given below Recombinant DNA technology, or genetic engineering,allows selected individual gene sequences to be transferred from an organism intoanother and also between nonrelated species Genetic engineering has been used

in agriculture and food industries in the past years in order to improve the formance of plant varieties (resistance to plagues, herbicides, and hydric or salinestresses), improve technological properties during storage and processing (firmness

per-of fruits), or improve the sensorial and nutritional properties per-of food products (starchquality, content of vitamins or essential amino acids) The organisms derived fromrecombinant DNA technology are termed genetically modified organisms (GMOs).Transgenic food is a food that is derived from or contains GMOs

The use of genetic engineering in the production of foods is constantly growingsince the past years as well as the concern in part of the public opinion This is due

to the increasing impact of this technology in foodstuff production, by one side, and

to the continued campaign against GMO crops lead by ecologist organizations, bythe other Claims about the advantages derived from GMO crops include those from

the biotechnology companies and most of the scientific community, stressing thebenefits for the agriculture and the food industry and the lack of scientific evidence

on any detrimental effects on human health On the other side, ecologists groups areconcerned about the impact of GM plants on human health and on the environment

In this context, most governments have dictated regulations on the use, spreading, andmarketing of GMOs, in order to regain the confidence of the consumers Owing to thecomplexity that entails the compositional study of a biological system such as GMO,the study of substantial equivalence as well as the detection of any unintended effectshould be approached with advanced profiling techniques, with the potential to extendthe breadth of comparative analyses However, there is no single technique currentlyavailable to acquire significant amounts of data in a single experimental analysis todetect all compounds found in GMOs or any other organism In consequence, multipleanalytical techniques have to be combined to improve analytical coverage of proteinsand metabolites Namely, the European Food Safety Authority (EFSA) (EFSA, 2006)has recommended the monitoring of the composition, traceability, and quality ofthese GM foods using advanced analytical techniques including omics techniques toprovide a broad profile of these GM foods (Levandi et al., 2008; Garcia-Villaba et al.,

2008, 2010; Sim´o et al., 2010; Garcia-Ca˜nas et al., 2011) The development of newanalytical strategies based on Foodomics will provide extraordinary opportunities toincrease our understanding about GMOs, including the investigation on unintendedeffects in GM crops, or the development of the so-called second-generation GM foods.Besides, Foodomics has to deal with the particular difficulties commonly found infood analysis, such as the huge dynamic concentration range of food components aswell as the heterogeneity of food matrices and the analytical interferences typicallyfound in these complex matrices

Nowadays, food is investigated not only as a source of energy but also as a tial health promoter As a result, food scientists and nutritionists have to face alarge number of challenges to adequately answer the new questions emerging fromthis new field of research One of the main challenges is to improve our limitedunderstanding of the roles of nutritional compounds at molecular level (i.e., theirinteraction with genes and their subsequent effect on proteins and metabolites) forthe rational design of strategies to manipulate cell functions through diet, which isexpected to have an extraordinary impact on our health (Garcia-Ca˜nas et al., 2010).The problem to be resolved is huge and it includes the study of the individual varia-tions in gene sequences, particularly in single nucleotide polymorphisms (SNPs), andtheir expected different answer to nutrients Moreover, nutrients can be considered

poten-as signaling molecules that are recognized by specific cellular-sensing mechanisms.However, unlike pharmaceuticals, the simultaneous presence of a variety of nutrientswith diverse chemical structures and concentrations and having numerous targets withdifferent affinities and specificities increases enormously the complexity of the prob-lem Therefore, it is necessary to look at hundreds of test compounds simultaneouslyand observe the diverse temporal and spatial responses

8 FOODOMICS: PRINCIPLES AND APPLICATIONS

Foodomics can be an adequate strategy to investigate the complex issues related

to prevention of future diseases and health promotion through food intake It is nowwell known that health is heavily influenced by genetics However, diet, lifestyle,and environment can have a crucial influence on the epigenome, gut microbiome,and, by association, the transcriptome, proteome, and, ultimately, the metabolome.When the combination of genetics and nutrition/lifestyle/environment is not prop-erly balanced, poor health is a result Foodomics can be a major tool for detectingsmall changes induced by food ingredient(s) at different expression levels A rep-resentation of an ideal Foodomics strategy to investigate the effect of food ingredi-ent(s) on a given system (cell, tissue, organ, or organism) is shown in Figure 1.2.Following this Foodomics strategy, results on the effect of food ingredient(s) atgenomic/transcriptomic/proteomic and/or metabolomic levels are obtained, makingpossible new investigations on food bioactivity and its effect on human health atmolecular level The interest in Foodomics also coincides with a clear shift in medicineand biosciences toward prevention of future diseases through adequate food intakes,and the development of the so-called functional foods It has been mentioned that it

NH2N N H N

N

N N

CH2NH C

N H H

H O

O O

H2N NH HO

Data analysis Data

and/or Biomarkers discovery Health benefits

known and scientifically based

SYSTEMS BIOLOGY

Metabolite expression

Protein expression

Data integration

Legal issues:

Claims on new functional foods approval

2DE MALDI-TOF-TOF LC-MS CE-MS

Cell, tissue, organ or organism under study (control vs treated with dietary ingredient(s))

FIGURE 1.2 Scheme of an ideal Foodomics strategy to investigate the health benefits fromdietary constituents, including methodologies and expected outcomes Modified from Ib´a˜nez

et al (2012) with permission from Elsevier

is probably too early to conclude on the value of many substances for health, and thesame can apply to other health relationships that are still under study In this regard,

it is interesting to remark that several of the health benefits assigned to many dietaryconstituents are still under controversy as can be deduced from the large number ofapplications rejected by the EFSA about health claims of new foods and ingredi-ents (EFSA, 2010; Gilsenan, 2011) More sound scientific evidences are needed todemonstrate the claimed beneficial effects of these new foods and constituents In this

sense, the advent of new postgenomic strategies as Foodomics seems to be essential

to understand how the bioactive compounds from diet interact at molecular and lular levels, as well as to provide better scientific evidences on their health benefits.The combination of the information from the three expression levels (gen, protein,and metabolite) can be crucial to adequately understand and scientifically sustain thehealth benefits from food ingredients To achieve this goal, it will be necessary tocarry out more studies to discover more polymorphisms of one nucleotide, to identifygenes related to complex disorders, to extend the research on new food products, and

cel-to demonstrate a higher degree of evidence through epidemiological studies based

in Foodomics that can lead to public recommendations Moreover, in spite of thesignificant outcomes expected from a global Foodomics strategy, practically thereare no papers published in literature in which results from the three expression levels(transcriptomics, proteomics, and metabolomics) are simultaneously presented andmerged Figure 1.3 shows the results from a global Foodomics study on the chemo-preventive effect of dietary polyphenols against HT29 colon cancer cells (Ib´a˜nez

et al., 2012) Figure 1.3 shows the genes, proteins, and metabolites that were fied (after transcriptomic, proteomic, and metabolomic analysis) to be involved in theprincipal biological processes altered in HT29 colon cancer cells after the treatmentwith rosemary polyphenols In order to demonstrate all its value, Foodomics stillneeds to be translated to methods or approaches with medicinal impact, for example,through the so-called personalized nutrition In this regard, data interpretation andintegration when dealing with such complex systems is not straightforward and hasbeen detected as one of the main bottlenecks

identi-In Foodomics, to carry out a comprehensive elucidation of the mechanisms of

action of natural compounds, specific nutrients, or diets, in vitro assays or animal

models are mainly used because (a) they are genetically homogeneous within aparticular assay or animal model and (b) environmental factors can be controlled.Moreover, these assays allow the study of certain tissues that would not be possible

to obtain from humans On the other hand, the main difficulty in the study of diets isthe simultaneous presence of a variety of nutrients, with diverse chemical structures,that can have numerous targets with different affinities and specificities Ideally, thefinal demonstration on the bioactivity of a given food constituent should be probed

by Foodomics based on a global omics study of the biological samples generatedduring a clinical trial

It is interesting to mention that there are still rather limited studies on the effect

of specific natural compounds, nutrients, or diet on the transcriptome/proteome/metabolome of organisms, tissues, or cells, being the number of review papers onthis topic higher than the number of research papers

1.3 FOODOMICS, SYSTEMS BIOLOGY, AND FUTURE TRENDS

Analytical strategies used in Foodomics have to face important difficulties derived,among others, from food complexity, the huge natural variability, the large number ofdifferent nutrients and bioactive food compounds, their very different concentrations,and the numerous targets with different affinities and specificities that they mighthave In this context, proteomics and metabolomics (plus transcriptomics) representpowerful analytical platforms developed for the analysis of proteins and metabolites(plus gene expression) However, “omics” platforms must be integrated in order

to understand the biological meaning of the results on the investigated system (e.g.,cell, tissue, organ) ideally through a holistic strategy as proposed by Systems Biology.Thus, Systems Biology can be defined as an integrated approach to study biologicalsystems at the levels of cells, organs, or organisms, by measuring and integratinggenomic, proteomic, and metabolic data (Panagiotou and Nielsen, 2009) SystemsBiology approaches might encompass molecules, cells, organs, individuals, or evenecosystems, and it is regarded as an integrative approach of all information at thedifferent levels of genomic expression (mRNA, protein, metabolite)

Although Systems Biology has been scarcely applied to Foodomics studies, itspotential is underlined by its adoption by other related disciplines For instance, Sys-tems Biology has been applied to understand the complexity of the processes in theintestinal tract (dos Santos et al., 2010) This study is based on human adult micro-biota characterization by deep metagenomic sequencing, identification of severalhundreds of intestinal genomes at the sequence level, identification of the transcrip-tional response of the host and selected microbes in animal model systems and inhumans, determination of the transcriptional response of the host to different diets inhumans, germ-free and gene knockout animals, together with different metabolomicsand proteomics studies The long-term goal is to understand how specific nutrients,diets, and environmental conditions influence cell and organ function, and how theythereby impact on health and disease This systems knowledge will be pivotal for thedevelopment of rational intervention strategies for the prevention of diseases such asdiabetes, metabolic syndrome, obesity, and inflammatory bowel diseases

The challenge in the combination of Foodomics and Systems Biology is not only

at the technological level where great improvements are being made and expected

in the “omics” technologies but also in improving our limited knowledge on manybiological processes that can have place at molecular level Last but not the least,bioinformatics (including data processing, clustering, dynamics, or integration of thevarious “omics” levels) will have to progress for Systems Biology to demonstrate allits potential in the new Foodomics discipline In this regard, it is also interesting tomention that the traditional medical world has often noted that although many of theomics tools and Foodomics approaches provide academically interesting research,they have not been translated to methods or approaches with medicinal impact andvalue because the data integration when dealing with such complex systems is notstraightforward

In the future, the combination of Foodomics and Systems Biology can vide crucial information on, for example, host–microbiome interactions, nutritional

pro-12 FOODOMICS: PRINCIPLES AND APPLICATIONS

immunology, food microorganisms including pathogens resistance, postharvest, plantbiotechnology, or farm animal production Besides, it is also foreseen the emerging

of other innovative approaches as, for example, green Foodomics (see the ter on this topic in this book), green systems biology (Weckwerth, 2011) or thehuman gutome

chap-ACKNOWLEDGMENTS

This work was supported by AGL2011-29857-C03-01 (Ministerio de Ciencia eInnovaci´on, Spain) and CSD2007-00063 FUN-C-FOOD (Programa CONSOLIDER,Ministerio de Educacion y Ciencia, Spain) projects

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Slater N, Wilson I (2007) Horizon Seminar, Foodomics? Why we eat, what we eat, andwhat’s next on the menu took place on Tuesday, 19 June, 2007 http://www.ceb.cam.ac.uk/pages/foodomics.html

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of genome sequence databases and advances in many areas Although much groundhas been covered, continued advances in methods, instrumentation, and computa-tional analysis is needed to get a complete analysis of biological systems Recently,Foodomics has been defined as a new discipline that studies food and nutritiondomains through the application of omics technologies in which MS techniques andproteomics are considered cornerstone players (Herrero et al., 2012).

With the rapid advances in protein analytical technologies in the early 1990s, itbecame possible to perform large-scale protein studies identifying the expression

of many of the proteins resolvable by two-dimensional electrophoresis (2-DE) Gelelectrophoresis was successfully developed for oligonucleotide sequencing in the late

1970 (Maxam and Gilbert, 1977) and it was also developed to separate proteins aboutthe same time (O’Farrell, 1975) In 1994 the term “proteome” was coined (Wilkins

Foodomics: Advanced Mass Spectrometry in Modern Food Science and Nutrition, First Edition.

Edited by Alejandro Cifuentes.

© 2013 John Wiley & Sons, Inc Published 2013 by John Wiley & Sons, Inc.

15

et al., 1996) and defined as the set of proteins expressed by the genome, and the study

of proteomes was named as “proteomics.”

In its short history, proteomics has lastly evolved Indeed, just a decade ago, allproteomic data were generated on instruments with low mass accuracy and resolution,and limited scan speed and sensitivity, compared to high-performance hybrid massspectrometers presently in common use

2.1.2.1 Separation Techniques by Chromatographic Methods Chromatographyhas been used for decades as a separation technique and, over time, has developed into

a sophisticated analytical technique The most used methods for protein separationare liquid chromatographic techniques (e.g., ion exchange, size exclusion, affinity,and reversed-phase (RP)), as well as electrophoretic separation in liquid-phase tech-niques (capillary isoelectric focusing, capillary zone electrophoresis, capillary gelelectrophoresis, and free-flow electrophoresis) Modern RP-HPLC utilizes a wideselection of chromatographic packing materials to separate proteins and peptides.The separation efficiency is determined by particle size and pore, surface area, sta-tionary phase, as well as the chemistry of the substrate surface The most popularcolumn packing is based on spherical silica particles where the surface is modified

by alkyl chains varying in length from C4to C18(Neverova and Van Eyk, 2005) The

C18bound phase is the most used, offering retention and selectivity for a wide range

of compounds containing different polar and non-polar groups on their surface C4and C8phases are used preferentially for separation of proteins and C18for peptides(Wagner et al., 2002)

2.1.2.2 Two-Dimensional Electrophoresis The introduction of sodium dodecylsulphate polyacrylamide gel electrophoresis (SDS-PAGE) allowed the use of theelectrophoretic mobility to study the occurrence of multiple protein forms Neverthe-less, single-dimension separations are inadequate for effectively resolving complexprotein mixtures Separation of proteins by 2-DE dates back to the 1950s (Smithiesand Poulik, 1956) and is still one of the most frequently used techniques to separatecomplex protein mixtures prior to characterization by MS The development of themodern 2-DE began with the combination of separation by isoelectric focusing (IEF)

in the first dimension and SDS-PAGE in the second dimension, a technique published

in 1969 by different authors (Dale and Latner, 1969; Macko and Stegemann, 1969).The most used methods to visualize proteins after 2-DE are Coomassie and silverstaining, both compatible with downstream MS analyses (Shevchenko et al., 1996)and whose limits of detection are at picomole and femtomole order, respectively(Miller et al., 2006) Colloidal Coomassie staining is more sensitive than the classicalCoomassie There are several fluorescent dyes to quantify the relative abundances

of protein amounts in 2-DE gels, such as Nile red, SYPRO Orange, SYPRO Red,and SYPRO Tangerine, but the ruthenium-based dye SYPRO Ruby, with sensitivitysimilar to silver staining and extended dynamic range, nowadays is one of the mostappropriate staining dyes in proteomics

INTRODUCTION 17

After electrophoresis separation and gel staining, statistical analysis is performedvia one of the powerful software packages specifically designed to match proteinspots of gel replicates for the different conditions, to compare protein patterns, and

to detect protein changes, both qualitative (presence/absence) and quantitative (spotintensities) (Rotilio et al., 2012)

The main limitation of this technique is that some proteins are not suitable forseparation by 2-DE Proteins with a molecular weight lower than 10 kDa or higherthan 150 kDa or with very basic isoelectric point (pI) are seldom detected usingconventional gels Moreover, hydrophobic proteins with low solubility cannot enterthe gels In addition, the detection of low-abundance proteins can be hindered byproteins with similar size and charge or by protein expression levels below thedetection limits of the technique (Monteoliva and Albar, 2004)

2.1.2.3 Difference in Gel Electrophoresis Differential proteomics, that is thecomparison of different proteomes or different samples such as healthy versus dis-eased, allows to perfom sensitive, accurate, and reproducible quantitative proteomicsstudies (Monteoliva and Albar, 2004) 2-DE technique does not accomplish this goal,because two different samples cannot be distinguished into the same gel Instead,difference in-gel electrophoresis (DIGE), a modified form of 2-DE, allows differentproteins to be quantified and even different isoforms of proteins that have differentmigration patterns on the 2-DE gel

DIGE technology will be explained in more detail below

2.1.2.4 Protein Identification by Mass Spectrometry

Identification by Two-Dimensional Electrophoresis Combined with Mass metry The classical workflow in MS-based proteomics includes the protein separa-tion by 2-DE and staining Afterward, gel images are analyzed and spots of interest arecut and de-stained to prevent staining interference with MS analysis Some samplesmay also need to be desalted and concentrated by using pipette tips containing C18or

Spectro-C4resin Then the proteins are digested being trypsin the most common enzyme used,

as it very specifically cleaves proteins at the C-terminal side of lysine and arginine,and generates peptides in the preferred mass range for subsequent MS analysis Onthe other hand, protein mixtures may be directly digested without previous separationand then peptide mixtures are analyzed by LC–MS

Ionization Techniques for Peptides and Proteins To measure the mass or, more

specifically, the mass-to-charge ratio (m/z) in a mass spectrometer, peptides and

proteins must first be ionized and transferred into the high vacuum system of theinstrument In the late 1980s, two methods were developed for the ionization athigh sensitivity: matrix-assisted laser desorption ionization (MALDI) (Karas andHillenkamp, 1988) and electrospray ionization (ESI) (Fenn et al., 1989)

Matrix-Assisted Laser Desorption Ionization MALDI is one of the ionizationtechniques more widely used in MS MALDI time-of-flight (MALDI-TOF) is one ofthe most commonly used mass spectrometers and consists of an ion source, a massanalyzer, and a detector The ion source has the purpose to convert sample moleculesfrom solution or solid phase into ionized analytes Firstly, analytes are co-crystallizedwith an organic matrix, such as␣-cyano-4-hydroxycinnamic acid and sinapinic acid,

on a metal target This MALDI matrix absorbs laser energy and transfers it to theacidified analyte, whereas the rapid pulsed laser is used to excite the matrix, whichcauses rapid thermal heating of the molecules and eventually desorption of ions intothe gas phase After ionization, the samples reach the TOF mass analyzer where

ions are separated on the basis of their m/z Ion motion in the mass analyzer can be

manipulated by electric or magnetic fields to direct ions to a detector, which registers

the number of ions at each individual m/z value (Rotilio et al., 2012) MALDI

ionization requires several hundred laser shots to achieve an acceptable noise ratio for ion detection, and the generated ions are predominantly singly charged(Sze et al., 2002)

signal-to-The drawbacks of this type of ionization are low shot-to-shot reproducibility andstrong dependence on sample preparation methods In general, the mass resolutionand accuracy of a MALDI-TOF mass spectrometer is not high enough to give anon-ambiguous identification of a peptide

The concept of MALDI has led to techniques such as surface-enhanced laserdesorption ionization (SELDI) that introduce surface affinity toward various proteinand peptide molecules

Electrospray Ionization Unlike MALDI, the ESI source produces ions fromsolution The use of ESI coupled to MS was introduced in 1989 and led to theNobel Prize for Chemistry in 2002 (Fenn et al., 1989) During ESI ionization, a highvoltage is applied between the emitter at the end of the separation pipeline and theinlet of the mass spectrometer Physicochemical processes of ESI involve creation ofelectrically charged spray, followed by formation and desolvation of analyte-solventdroplets is aided by a heated capillary and, in some cases, by heated gas flow at themass spectrometer inlet (Steen and Mann, 2004) An important development in ESItechnique includes micro- and nano-ESI, in which peptide mixtures are sprayed intothe mass spectrometer at a very low flow rates improving the method’s sensitivity

Peptide Mass Fingerprinting The development of new MALDI instruments allows

to know sequence of peptides, where a MALDI source is coupled to a double flight section (MALDI-TOF-TOF), a hybrid quadruple TOF or an ion trap MALDI-TOF/TOF MS is widely used in proteomics to identify proteins by a process calledpeptide mass fingerprinting (PMF) The main limitations of the MALDI-based PMFapproach are that proteins must be completely sequenced and annotated in databases;

time-of-it cannot identify proteins containing post-translational modifications (PTMs); time-of-itrequires a complete protein separation and it is not appropriate for proteins withextensive cross-similarity

EMERGING METHODS IN PROTEOMICS 19

Tandem Mass Spectrometry Tandem mass spectrometry (MS/MS) is a process inwhich an ion formed in an ion source is mass-selected in the first phase, reactedand fragmented, and then the charged products from the reaction are analyzed in thesecond phase The high precision of MS spectrometric measurements can analyzesmall molecules and distinguish closely related species, and MS/MS can providestructural information on molecular ions that can be specifically isolated on the basis

of their m/z and fragmented in the gas phase within the instrument.

In LC–MS/MS, peptides generated from the digestion of complex mixtures ofproteins are separated on the basis of their hydrophobicity and introduced into themass spectrometer, in most of the cases directly via online ESI The ESI source can becoupled to several mass analyzers, as quadrupole, ion trap, orbitrap, or Fourier trans-form ion cyclotron resonance system, whose accuracy and sensitivity is extremelydifferent (Yates et al., 2009) After ESI and detection, the final step in this process isthe identification of the proteins by the MS/MS fragmentation spectra using specificdatabases

Sample preparation is critically important in proteomics experiments Less solubleproteins are difficult to study and the detection of low-abundance proteins is a greatchallenge for proteomics

Adjuvants and contaminants, such as salts, detergents, or stabilizers, can interferewith the results of mass spectrometric analysis In case of LC coupled to ESI-MS, saltsand detergents can be removed online within the HPLC setup (e.g., guard column

or trapping column) For higher concentrations and for MALDI-MS applications,spinning columns, dialysis, or precipitation are the methods which are mostly applied.Nevertheless, to avoid losses or modifications of the proteins, sample preparation stepshave to be limited to the minimum steps needed

The field of MS-based proteomics can be broadly categorized into two fundamentalapproaches: the increasingly popular top-down proteomic approach that focuses onthe direct analysis by MS of entire intact proteins after being subjected to gas-phasefragmentation; and the more widely used bottom-up proteomic approach that focuses

on the analysis of peptides obtained after proteolytic digestion of proteins (Fig 2.1).With top-down analysis, all PTMs will be subjected to analysis, while bottom-upanalysis may skip the fragments with these types of modifications

2.2.1.1 Bottom-up Proteomics Bottom-up analyses are performed by initial teolytic digestion of the protein of interest, followed by LC–MS analysis of the

pro-FIGURE 2.1 Representation of top-down and bottom-up proteomics approaches.

resultant peptides whose sequences are used to identify the corresponding proteins.The enzyme most used for protein digestion is trypsin, which is very well suited

to downstream analysis by the most common MS and tandem MS/MS techniques.However, information regarding PTMs or protein isoforms could be missed, and it isoften worth considering other proteolytic enzymes or applying a panel of enzymes(Swaney et al., 2010) The digestion of proteins greatly increases the complexity

of samples and it is essential to separate them into manageable, reproducible tions In addition, pre-analytical sample processing must be considered especially forhigh-complexity samples for large-scale analyses

frac-EMERGING METHODS IN PROTEOMICS 21

Experimentally determined peptide masses that differ from those predicted fromthe primary protein sequence allow for identification of modified regions within theprotein (Henzel et al., 1993) Analysis of these peptide ions by MS/MS may beused for further characterization of the modification, including its localization to aspecific site within the peptide sequence It is common, however, that some of thepeptides resulting from bottom-up digestion strategies are not observed upon massspectrometric analysis due to their poor chromatographic retention behavior, or inef-ficient ionization (Kapp et al., 2003) The main pre-fractionation methods used areSDS-PAGE, size-exclusion, anion-exchange, cation-exchange, lectin-affinity chro-matography, RP-LC in basic media, free solution IEF, and high-abundance proteindepletion

Some of the advantages of the bottom-up approach include better front-end aration of peptides compared with proteins and higher sensitivity than the top-downmethod Drawbacks of the bottom-up approach include limited protein sequencecoverage by identified peptides, loss of labile PTMs, and ambiguity of the origin forredundant peptide sequences (Yates et al., 2009)

sep-2.2.1.2 Top-down Proteomics Top-down MS method is used for the sive identification and characterization of the total number and type of cotranslationaland PTMs that are present within a protein of interest This top-down approach isbased on the mass difference between the experimental and predicted masses of theintact protein However, determination of an intact protein mass alone, even at thehighest resolution and mass accuracy provided by modern MS instrumentation, isgenerally not useful for the characterization of a modified protein, due to the inability

comprehen-of unambiguously localizing the modification to a specific site within the proteinsequence (Lee et al., 2002) In the top-down MS/MS-based strategies, ions derivedfrom the intact protein are isolated following their initial mass analysis, and thensubjected to fragmentation As the entire sequence of the protein is available, proteinidentification may potentially be achieved in a single step, including the characteri-zation of any PTMs (Sze et al., 2002)

Compared with bottom-up approaches, the higher sequence coverage of top-downexperiments reduces the ambiguities of the peptide-to-protein mapping, which allowsfor identification of the specific protein isoforms (Uttenweiler-Joseph et al., 2008).However, there are technological limitations to the top-down method such as front-end separation of intact proteins is more challenging than the separation of peptidemixtures and methods to fragment large proteins are more complex

In order to successfully apply these methods, it is necessary to use instrumental

or chemical approaches for determining the charge states and masses of the ply charged product ions resulting from the dissociation of large multiply chargedprotein ions, and develop multistage tandem MS or alternative ion dissociation meth-ods to maximize the sequence coverage obtained from these dissociation reactions(Scherperel and Reid, 2007)

multi-Further advances of protein characterization using top-down approaches can bemade with the development of high-resolution mass analyzers

FIGURE 2.2 Workflow of protein quantitation MudPIT, multidimensional protein cation protein; SCX, strong cation exchange; RP, reversed phase.

In addition to the classical methods of 2-DE and DIGE, MS-based quantificationmethods have gained increasing popularity There are two broad groups of quantitativemethods in MS-based proteomics: relative and absolute quantitative proteomics

In addition, quantitative proteomics can be classified into two major approaches:differential stable isotope labeling and label-free techniques (Fig 2.2)

The proteomic quantification methods utilizing dyes, fluorophores, or radioactivityhave provided very good sensitivity, linearity, and dynamic range, but they suffer fromshortcomings such as that they require high-resolution protein separation typicallyprovided by 2-DE gels, which limits their applicability to abundant and solubleproteins; and they do not allow the identification of the proteins

Labeling methods include labeling of two or more different samples (i.e., healthyand diseased) either with the light isotope or with the heavy isotope to create a specificmass tag that can be recognized by a mass spectrometer, and the determination ofthe ratio of heavy to light allows a comparative analysis of the relative amounts ofproteins in the samples These isotope labels can be introduced into amino acids ofproteins or peptides (a) metabolically (such as SILAM and SILAC), (b) chemically(such as ICAT, ICPL, iTRAQ, and TMT), (c) enzymatically (18O/16O), or (d) as

an external standard using spiked synthetic peptides In contrast, label-free methodsaim at comparing two or more experiments on the basis of the signal intensity

EMERGING METHODS IN PROTEOMICS 23

for any given peptide or at counting the spectra identified for each sample by thesearch engine

2.2.2.1 Quantitative Proteomics by Difference In-Gel Electrophoresis DIGEallows for simultaneous separation of up to three samples on one gel These samples,usually two different samples (control vs experimental conditions) and one inter-nal standard, are covalently labeled separately with three fluorescent cyanine dyes(CyDye2, CyDye3, and CyDye5), each with a unique excitation/emission wavelength(to discriminate the protein from each sample), then combined and run together (mul-tiplexed) on the same 2-DE gel Typically, Cy3 and Cy5 are used for labeling samplesand Cy2 is used as an internal standard The internal standard is a pooled mixturecontaining an equal aliquot of all test samples facilitating accurate inter-gel match-ing of spots; it allows for data normalization and minimizes gel-to-gel experimentalvariability, leading to the measurement of subtle changes in protein abundance Pro-tein spots corresponding to proteins of different samples can then be visualized byscanning and the differential analysis software analysis enables relative quantitation

of the labeled proteins (Fernandez and Albar, 2012; Richard et al., 2006)

DIGE offers clear advantages over the gel-to-gel comparisons because the differentsamples are run on the same 2-DE gel and hence the same spots will comigrate Anal-ysis is performed using software such as GE DeCyder that includes a co-detection

algorithm and results are presented using univariate statistics (Student’s t-test)

Label-ing with DIGE fluors is extremely sensitive, but the relative high cost of the reagents,equipment, and software, limits a wide application of the technique

2.2.2.2 Differential Stable Isotope Labeling Stable isotope labeling was duced into proteomics in 1999 by three independent laboratories (Gygi et al., 1999;Oda et al., 1999; Paˇsa-Toli´c et al., 1999) Given that a mass spectrometer can rec-ognize the mass difference between the labeled and unlabeled forms of a peptide,quantification is achieved by comparing their respective signal intensities

intro-In Figure 2.3 there is a representation of the stable isotope labeling methods morewidely used in proteomics

The first stable isotope labeling approach was based on a class of reagents termedisotope-coded affinity tags (ICATs) in which the sample is chemically reacted withlight or heavy pairs of an isotope tag, leading to a cysteine-specific tagging of intactproteins followed by proteolytic digestion This technique provides an alternativemethod to the 2-DE-based approaches, but the main drawback is that only proteinscontaining cysteines can be quantified

The cleavable version of this reagent (cICAT) contains nine13C instead of terium and an acid-cleavable biotin moiety The advantages of this approach are thatslightly different LC retention times due to deuterium no longer occurred and thepotential confusion with double ICAT labeling being the same mass shift as oxidationwas removed Also, biotin cleavage improved the quality of the spectra and led to theidentification of more proteins (Elliott et al., 2009)

deu-Most labeling-based quantification approaches have potential limitations Theseinclude increased time and complexity of sample preparation, requirement for higher